What is Repeated Measures Design? - Definition & Example

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  • 0:04 Repeated Measures Design
  • 1:33 Benefits
  • 2:35 Challenges
  • 3:12 Example
  • 4:10 Lesson Summary
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Lesson Transcript
Instructor: Betsy Chesnutt

Betsy teaches college physics, biology, and engineering and has a Ph.D. in Biomedical Engineering

Repeated measures design is important in many types of scientific research. In this lesson, you'll learn how to use repeated measures design and explore some of its strengths and weaknesses.

Repeated Measures Design

Susannah works for a company that is in the process of developing some new soda flavors, and she is responsible for designing a taste test to determine which flavor customers might like the best. How can she design this experiment? She could recruit several groups of people and have each group taste a different soda, then rate the soda based on how well they thought it tasted. This is a type of experimental design known as independent measures, and while it might work, there are a few problems with using it in this experiment.

The main problem is that she would have a hard time distinguishing which soda people liked the best, since there were different groups of people tasting each one. There's sure to be a lot of variability in taste between people. Because of this inherent variability, Susannah would need a lot of people to taste the sodas in order to reach any kind of statistically significant conclusion.

There's another way that this experiment could be designed, however. Experiments using repeated measures design, sometimes also called within-subject design, make measurements using only one group of subjects, where tests on each subject are repeated more than once after different treatments.

To taste test the new sodas, Susannah could gather a group of people and have them go through multiple taste tests. The group could drink and rate the new sodas, then drink and rate a flavor that's already popular (to serve as a control). Susannah can change the order of these treatments, but the basic idea is all subjects are exposed to all of the treatments. We'll see how this approach can make the best of limited resources while still offering powerful results.


Why might a scientist want to conduct an experiment using repeated measures design? There are many reasons. First, it's often cheaper and easier to conduct an experiment in this way because it's possible to detect statistical differences with a smaller number of subjects. Repeated measures design means that you don't have to have separate control groups and treatment groups because the same group is both the control and is exposed to all the treatments, just at different times.

In addition, it's often very difficult to control for variables that may be different between subjects, such as the variation in taste between subjects in the soda taste test. Repeated measures design reduces the effect of this variability because the same subjects are used throughout the experiment. This allows the researcher to make powerful statistical conclusions with a relatively small set of subjects.

Finally, repeated measures design allows the effect of the treatment to be measured over time, and at multiple different times, using the same subjects. This is important in studies that follow a single group of people over time, known as a longitudinal study.

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